This book will provide a comprehensive overview on human action analysis with randomized trees. It will cover both the supervised random trees and the unsupervised random trees. When there are sufficient amount of labeled data available, supervised random trees provides a fast method for space-time interest point matching. When labeled data is minimal as in the case of example-based action search, unsupervised random trees is used to leverage the unlabelled data. We describe how the randomized trees can be used for action classification, action detection, action search, and action prediction. We will also describe techniques for space-time action localization including branch-and-bound sub-volume search and propagative Hough voting.
Reihe
Sprache
Verlagsort
Verlagsgruppe
Illustrationen
30
30 farbige Abbildungen
VIII, 83 p. 30 illus. in color.
Dateigröße
ISBN-13
978-981-287-167-1 (9789812871671)
DOI
10.1007/978-981-287-167-1
Schweitzer Klassifikation
